dage, and Connell 1998). These qualifiers could betemporal (for example, “pain started two days ago”),spatial (“pain in the epigastric region”), or other asso-ciations (“pain after eating fatty foods”). Implicit inthis task is the human’s ability to extract conceptsand their associated qualifiers from the natural lan-guage narrative. For example, the above qualifiersmight have to be extracted from the sentence “Thepatient reports pain, which started two days ago, inthe epigastric region especially after eating fattyfoods.”The computer system needs to perform a similaranalysis of the narrative. We use the term factor todenote the potentially relevant observations along

Figure 3. Visualization of an Assertion Graph.

By convention, input factors are placed at the top and hypotheses at the bottom with levels of inference factors in between.

indicates

patient’sSubstantiaNigra isaffectedA 63-year-old patientis sent to theneurologist with ...resting tremor ... Whatpart of his nervoussystem is most likelyaffected?

An edge represents a relation
between the connected
statements. Agents make
assertions about the truth of
these relations with
con;dences. Edge width
represents that con;dence.
Gray level represents the
amount of belief ;ow.

A node represents a statement.
Types of statements are input
factors, inferred factors and
hypotheses or answers. Border
strength visually represents
“belief” the factor is true in
context.